Optimal Time Allocation Research Articles

An actuator space optimal kinematic path tracking framework for tendon-driven continuum robots: Theory, algorithm and validation

Path tracking of continuum robots is a fundamental and crucial problem across various applications. In this article, we address this problem by focussing on three aspects. Firstly, we propose an efficient multi-solution inverse kinematics solver for three-section constant curvature robots by bridging the theoretical reduction and the numerical correction. Secondly, we derive a linear tendon-driven actuation model, establishing the connection between the robot configuration space and the actuator space. With this model, we achieve optimal distance planning and optimal time allocation considering the constraints of actuator velocity and acceleration, generating a continuous trajectory directly in the actuator space. Finally, we present our kinematic path tracking framework, which includes offline optimal trajectory planning and online feedforward and feedback control. Experiments are conducted both in simulations and in the real world on our three-section tendon-driven continuum robot. The experiments validate the increased efficiency, higher success rates, and accessibility of multiple solutions offered by our inverse kinematics solver, as well as the optimality in distance planning and time allocation in the actuator space. Performance improvements in tracking accuracy are demonstrated through comparative experiments and the application of our framework in path tracking tasks with obstacles is presented through a case study.

Powered–coasting–powered multi-phase mission reconfiguration method for launch vehicles under power system failures

For the final stage of a launch vehicle with powered–coasting–powered multi-phase flight, this paper investigates the joint reconfiguration method to determine subsequent flight trajectory and degraded orbit after power system failure in the first powered phase. While power system failures due to mass–flow–rate drop have been thoroughly studied in the existing literature, this paper focuses on the more challenging specific impulse drop failures, which result in loss of total launcher energy. This paper aims to design a fault-tolerant guidance method with onboard potential and to analyze the survivability and characteristics of the launcher in the event of such a failure. In the problem modeling, the strong nonlinearity of the orbital elements as terminal constraints is eliminated by analyzing the orbital properties in the orbital coordinate system to establish the primal trajectory optimization problem. For this multi-phase trajectory optimization problem, a joint optimization algorithm for the degradation orbit and the flight trajectory, based on convex optimization and Radau pseudospectral method, is designed to achieve autonomous mission reconfiguration. The algorithm introduces the relaxation–penalization idea, where the terminal constraints are relaxed and penalized in the performance index, allowing the algorithm to adaptively form an optimal degradation circular or elliptical orbit based on the remaining capacity of the launch vehicle. Simulation experiments demonstrate the effectiveness and superiority of the mission reconfiguration algorithm. Finally, the paper presents the first analysis of the optimal allocation of flight time between the first powered phase, the coasting phase, and the second powered phase in a propellant depletion scenario following the launcher power system failure.

Optimal Time and Power Allocation for Phase-Shift Configuration and Downlink Channel Estimation in RIS-Aided Systems

Optimal Time and Power Allocation for Phase-Shift Configuration and Downlink Channel Estimation in RIS-Aided Systems

ЭФФЕКТИВНОЕ РАСПРЕДЕЛЕНИЕ ВРЕМЕНИ МЕЖДУ УЧЕБОЙ, РАБОТОЙ И ЛИЧНОЙ ЖИЗНЬЮ У СТУДЕНТОВ

The article discusses the problem of effective time management by students, factors influencing time management, strategies for optimizing time allocation. The results of a practical study of time distribution by university students are presented

Analysis on Academic and Employment Cognitions of Students Majoring in Marketing at Ningde Normal University

The content of marketing major includes human resources, finance, sales, logistics and other management contents in the field of management, with some hybridity. Insufficient cognition on the major and one's own psychological characteristics affects the optimal allocation of time during college years, which in turn affects academic performance and employment. Through questionnaire surveys of current students and interviews of graduated students majoring in marketing at Ningde Normal University, this paper analyzes students' academic and employment cognitions. Some lower-grade students majoring in marketing have vague cognitions about their major. In addition to the unclear cognitions about the major, like students of other majors, a certain proportion of students also lack clear cognitions about their own psychological characteristics. After students start learning marketing, it is necessary to improve their cognitions about the major through various means. Offering career planning courses in the first semester enables students to cognize the major and themselves earlier, so that they can engage in purposeful learning and training during college, which is beneficial for their academic development and employment.

Outage performance and energy efficiency optimization of wireless-powered millimeter-wave sensor networks

AbstractWith the widespread use of wireless sensor networks, one of the most pressing concerns is extending the lifetime of the sensors. By deploying directional antenna arrays, millimeter wave (mmWave) is a possible candidate for wireless energy transfer (WPT). This paper investigates a beneficial combination of WPT and data transmission in a typical mmWave sensor network with Rayleigh channels, where a transmission interval can be divided into two sub-intervals. During the first sub-interval, one hybrid access point (HAP) employs beamforming techniques to transfer energy for serving multiple sensors within the service sector. The sensors then transmit their individual signal in turn to the HAP based on time division multiple address (TDMA) strategy by using the whole harvested energy. According to stochastic geometry, the exact and approximate expressions of beam outage probability for the considered system are determined, respectively. The optimal time allocation of energy harvesting and data transmission for sensors is examined in order to maximize the energy efficiency of the system. The optimization problem can be translated into corresponding parametric form, and the resulting optimization problem can be solved using the Lagrange dual method with Karush–Kuhn–Tucker (KKT) conditions. The numerical results show the variation trend of the beam outage probability under various parameters and verify the accuracy of the theoretical analyses. Furthermore, the simulation results illustrate that the proposed optimal time allocation strategy can significantly enhance the overall energy efficiency of the system compared with a similar scheme.

Problematika Penerapan Kurikulum Merdeka Dalam Mata Pelajaran Pendidikan Agama Islam

This study aims to analyze the implementation of the Merdeka Curriculum in Islamic Religious Education (PAI) learning at SMP Negeri 2 Diwek and its problems. A qualitative approach was used with data collection techniques through in-depth interviews and observations. The results showed that the Merdeka Curriculum had been implemented for one year through student-centered learning, the development of the Pancasila Student Profile, and the provision of flexibility in choosing teaching materials. The obstacles found included the diversity of student characteristics, low motivation, limited facilities and infrastructure, difficulties in assessment, teacher workload, and limited learning time. Recommended solutions include mapping student characteristics, differentiated instruction, increased motivation, development of instructional media, assessment training, coordination to reduce teacher burden, optimization of time allocation, integration of PAI values, and student guidance services. Collaborative implementation of these solutions can improve the quality of the Merdeka Curriculum implementation in PAI learning to realize national education goals.

Optimal Allocation of Layover Time in a Smart DC Railway Metro Traction System

Optimal Allocation of Layover Time in a Smart DC Railway Metro Traction System

Throughput maximization scheme of the IRS-aided wireless powered NOMA systems

The computation complexity of the existing resource allocation schemes to maximize sum throughput is very high for intelligent reflecting surface (IRS)-assisted wireless powered non-orthogonal multiple access (NOMA) system. Therefore, a low complexity resource allocation method to maximize sum throughput is considered by joint optimizing phase shifts and time allocation. Firstly, to reduce the variables that need to be optimized, we derive the problem with only phase shifts as variables, and further deduce optimization problem of phase shifts only for downlink wireless energy transmission (WET) process. Then, the problem of phase shifts for WET process is solved directly by transforming multi-variable optimization problem into that with single variable, and the phase shifts for the uplink wireless information transmission process are got as well with given phase shifts for WET process. Finally, with given phase shifts, the optimal time allocation is obtained by using the function extremum method. Theoretical analysis demonstrates that the proposed scheme has low computational complexity, and the simulation results show that sum throughput of the proposed scheme is no less than that of the existing schemes in the same scenario.

Performance Analysis of a WPCN-Based Underwater Acoustic Communication System

Underwater acoustic communication (UWAC) has a wide range of applications, including marine environment monitoring, disaster warning, seabed terrain exploration, and oil extraction. It plays an indispensable and increasingly important role in marine resource exploration and marine economic development. In current UWAC systems, the terminal nodes are usually powered by energy-limited batteries. Due to the harshness of the underwater environment, especially in the ocean environment, it is very costly and difficult, even impossible, to replace the batteries for the terminal nodes in UWACs, which results in the short lifetime and unreliability of the terminal nodes and the systems. In this paper, we present the application of a wireless powered communication network (WPCN) to the UWAC systems to provide an auxiliary and convenient energy supplement for solving the energy-limited problem of the terminal nodes, where the hybrid access point (H-AP) transfers energy to the terminal nodes in the downlink. In contrast, the terminal nodes use the harvested energy to transmit the information to the H-AP in the uplink. To evaluate the proposed WPCN-based UWAC systems, we investigate the performance of the average bit error rate (BER), outage probability, and achievable information rate for the systems in a frequency-selective sparse channel and non-white noise environment. We derive the closed-form expression for the probability density function (PDF) of the received signal-to-noise ratio (SNR). Based on this, we further derive novel closed-form expressions for the average BER and the outage probability of the systems. Numerical results confirm the validity of the proposed analytical results. It is shown that there exists an optimal signal frequency and time allocation factor for the systems to achieve optimal performance, and a larger optimal time allocation factor is preferred for a smaller hybrid access point (H-AP) transmit power or a larger transmission distance, while a smaller optimal signal frequency is required for a larger transmission distance.

An intelligent age of information based self‐energized UAV‐assisted wireless communication system

AbstractInternet‐of‐things is an enabling technology in the fourth‐generation industrial revolution. The freshness of the data sent by a sensor node (SN) is an important parameter in the Internet‐of‐things, unlike the throughput in cellular communications. A relatively new performance metric named age of information (AoI) is used in this paper to quantify the freshness of the data. The SN, located in the transport infrastructure, harvests energy from radio frequency signals transmitted by the FD‐UAV. This is used to transmit real‐time sensor observations to the data sink via FD‐UAV. The SN generates an update after replenishing the battery and transmits it by using the harvested energy. A closed‐form expression for average AoI is derived as a function of time allocated for energy harvesting. The optimal time allocation for energy harvesting that maximizes the freshness of data update is identified. A deep learning technique namely long‐short term memory is used to predict the average AoI. Simulation results demonstrate the usefulness of the performance bounds in terms of the freshness of data updates.

Optimal design of integrated visible light communication and positioning system with energy harvesting.

In this paper, an optimization scheme that can simultaneously transmit communication information, positioning the information and energy in a visible light communication and positioning (VLCP) system with energy harvesting is proposed. The time switching-power splitting (TS-PS) method is applied, where the power and time allocation factors are defined as optimization variables, so that the system can maximize the harvested energy under the constraints of the information rate and positioning error. The multi-verse optimization (MVO) algorithm is introduced to obtain the optimal power and time allocation. In addition, the performance of the integrated system using the TS-PS method is investigated and compared with that using other conventional methods. The results show that a maximized harvested energy solution using the TS-PS method can harvest the most energy. Moreover, the effects of main external environment conditions, namely, the room height and field of view (FoV) of a photo diode (PD) on the system performance are also analyzed. The increase of the room height and FoV of the PD reduces the harvested energy, but does not change the information rate and positioning accuracy in the optimized system adopted in this paper.

Stackelberg Game-Based Multiple Access Design for Intelligent Reflecting Surface Assisted Wireless Powered IoT Networks

This paper integrates an intelligent reflecting surface (IRS) into a wireless powered Internet-of-Things (IoT) network, where IoT devices need to harvest energy from an energy station (ES) before transmitting their monitoring data to an access point. An IRS is invoked to improve energy and spectral efficiency by changing propagation environment. Considering that the ES and IoT devices come from different operators, IoT devices need to provide monetary payment in exchange for the ES’s charging before implementing nonlinear energy harvesting. We build this energy interaction via Stackelberg game under three multiple access schemes, i.e., IRS-assisted time division multiple access (IRS-TDMA), IRS-assisted non-orthogonal multiple access (IRS-NOMA), and IRS-assisted frequency division multiple access (IRS-FDMA). To solve the common follower game among the three schemes, we first employ an alternating optimization (AO) algorithm with Majorization-Minimization (MM) to alternately optimize the energy beamforming and energy phase shifts, and then derive the optimal ES transmit power. For the leader game of IRS-TDMA, the optimal time allocation and optimal information phase shifts are first derived in closed form through Lagrange dual method and triangular inequality, respectively. On this basis, an AO algorithm is developed to optimize energy price and energy transfer time alternately. Similar procedures are also used to solve the leader games for IRS-NOMA and IRS-FDMA. Simulation results show that IRS-NOMA and IRS-FDMA achieve the same utilities for the ES and IoT devices. Due to IRS time selectivity, IRS-TDMA is more energy and spectral efficient than IRS-NOMA and IRS-FDMA, and this advantage is more pronounced in higher numbers of IRS elements and IoT devices.

Optimal Time Allocation for Backscatter-Aided Relay Cooperative Transmission in Wireless-Powered Heterogeneous CRNs

Nowadays, backscatter, radio-frequency (RF) energy harvesting (EH), and cognitive radio technologies have been widely applied in Internet of Things (IoT) to address the issues of energy supply and spectrum scarcity. This paper focuses on the throughput maximization problem of backscatter-aided wireless-powered heterogeneous cognitive radio networks (WPHetCRNs), where two types of secondary transmitters (STs), i.e., the STs with backscatter units (STBs) and the STs with RF-EH units (STEs), coexist. The STBs operate in the ambient backscatter (AB) mode, and the STEs operate in the harvest-then-transmit (HTT) mode. Inspired by the potential benefits of cooperations between different users, we propose a backscatter-aided cooperative relay transmission (BaCRT) strategy to improve the sum-throughput of the secondary users (SUs). The main idea is that when the licensed spectrum of the primary users (PUs) is busy, the STBs first help to relay the primary data via the passive relay mode, and then transmit the secondary data via the AB mode, while the STEs harvest energy in the HTT mode. With the help of relaying, the target throughput of the PUs could be met in shorter duration and the licensed spectrum could become idle more quickly. When the licensed spectrum becomes idle, the STEs transmit data in the HTT mode. The goal of this paper is to identify the optimal time allocation among the passive relay mode, AB mode, and data transmission of HTT mode that maximizes the sum-throughput of the SUs. To reach this goal, we first investigate the single-ST case for each type and derive the closed-form solution of the optimal time allocation. We then extend to the multiple-ST case for each type, where three scenarios are classified with respect to the fairness issue of the STBs. We prove that the sum-throughput maximization problem is convex in each scenario, and employ the block coordinate descent and gradient descent iterative algorithms to solve the problem. Numerical results show that the proposed BaCRT strategy significantly improves the sum-throughput of the SUs compared with other strategies.

Optimizing Worst Case Data Freshness in RF-Powered Networked Embedded Systems

Maintaining real-time data freshness plays a critical role in ensuring system correctness and optimizing the system performance in networked embedded systems (NESs). To quantitatively measure the freshness of the collected real-time data, the concept of Age of Information (AoI) has been extensively studied in recent years. This article explores how to minimize the worst-case AoI of real-time data in RF-powered NESs. In such systems, one hybrid access point (HAP) transfers wireless power to a set of distributed sensor nodes, and in the meantime, receives the information from these sensor nodes. We utilize the metric of AoI to measure the data freshness and present a comprehensive analysis of the worst-case AoI of the real-time data in the target system. Based on the analysis, an optimal energy schedule solution is designed to judiciously determine individual sensor nodes’ energy and time allocation to minimize the worst-case AoI. Considering the varying importance of different information and sensor nodes in the target system, we further propose the optimal time and energy allocation scheme for minimizing the weighted worst-case AoI. A multi-node RF-powered NES testbed is implemented to validate the functional correctness of our solutions. The results show that our solutions significantly outperform the state-of-the-art solutions, reducing the worst-case AoI and weighted worst-case AoI by 69.3% and 75.1% on average, respectively.

Energy-Efficient Beamforming and Resource Optimization for STAR-IRS Enabled Hybrid-NOMA 6G Communications

In this manuscript, we propose an energy-efficient optimization framework for a multi-cluster simultaneous transmitting and reflecting intelligent reflecting surfaces (STAR-IRS) enabled time-division multiple-access (TDMA) based hybrid-NOMA system to realize the future sixth-generation (6G) wireless communication systems. Specifically, the energy-efficiency maximization is achieved by optimizing the successive-interference cancellation (SIC) decoding order, time-allocation, and active-beamforming vectors at the transmitter, as well as transmission and reflection coefficients at the STAR-IRS under quality-of-service (QoS), conservation of energy, time-allocation, phase-shifts, and SIC-decoding constraints. Moreover, the proposed alternating optimization algorithm tackles the considered highly non-convex optimization problem in four steps. In first step, for computing the SIC-decoding order of NOMA users, an efficient optimization technique is proposed which maximizes the sum of combined channel gains by optimizing the transmission and reflection beamforming vectors of the considered STAR-IRS assisted hybrid-NOMA system. Further, in second step, an optimal time-allocation for each cluster in transmission and reflection region is computed for given SIC-decoding order. With decoding order and time-allocation in hand, active-beamforming vectors are computed by exploiting the sequential-convex approximation (SCA) and second-order-conic programming (SOCP) in third step. Finally, in the fourth step, the transmission and reflection coefficients of STAR-IRS are computed by transforming the non-convex optimization problem into a semi-definite programming (SDP) problem. Th numerical simulation results demonstrate that the proposed optimization framework exhibits an efficient energy efficiency performance and converges within a few iterations.

Joint Optimal Data Collection Scheduling and Time Allocation in Full-Duplex WP-IoT Networks

This paper considers a full-duplex wireless powered internet of things (WP-IoT) network, supporting simultaneous wireless power transfer of a hybrid access point in the downlink and collected data transfer of devices in the uplink. Compared to existing works where the data collection process is mostly ignored, the problem of joint data collection scheduling and time allocation is investigated under two objectives, i.e., total throughput maximization subject to a total time constraint and total time minimization subject to minimum collected data constraints. For both objectives, the optimal solution is derived in closed-form. It is revealed that the proposed algorithms outperform various baseline algorithms in existing literature.

Performance analysis and optimization for cellular two-way relay networks with cooperative NOMA transmission

This paper proposes a cooperative non-orthogonal multiple access (NOMA) based two-way transmission scheme for a two-user cellular system, in which a base station (BS) exchanges information with a directlink user and an indirect link user. With superimposition coding, physical-layer network coding (PLNC) and successive interference cancellation, the BS and the two users are able to exchange messages within three time slots. We derive the sum-rate upper bound of the proposed scheme and investigate the optimal time and power allocations to maximize the sum-rate bound. Numerical results demonstrate that the derived bound is tight and the proposed scheme can improve the sum-rates significantly as compared with existing NOMA-based schemes.

Securing Multiuser Communications via an Energy Harvesting Node: Jammer or Relay?

In this paper, we study the secure communication problem of a wireless multiuser network consisting of a base station (BS), multiple users, and an energy harvesting (EH) node in the face of an eavesdropper. We focus on the question that which role the EH node plays, as a friendly jammer or as a cooperative decode-and-forward (DF) relay. Accordingly, we propose two EH node aided multiuser scheduling schemes to help the secure communications between BS and multiple users, i.e., the EH jammer aided transmission (EHJT) scheme where the EH node acts as a friendly jammer and the EH relay aided transmission (EHRT) scheme where the EH node acts as a cooperative DF relay. For comparison purposes, the direct transmission (DT) scheme is also presented. We analyze the security-reliability trade-off (SRT) performance of the proposed EHJT and EHRT schemes as well as the DT scheme in terms of deriving their exact and asymptotic expressions of outage and intercept probabilities. Additionally, we propose an iterative algorithm based on the golden search to determine the optimal time allocation factor (OTAF) for the sake of minimizing the sum of outage and intercept probabilities for the proposed EHJT and EHRT schemes. Numerical results show that the EH node can improve the SRT performance of the multiuser network more significantly as a friendly jammer than as a cooperative DF relay. It is also shown that the best SRT performance of the EHJT and EHRT schemes can be achieved by adjusting the signal-to-noise ratio (SNR) and time allocation factor.

Low-Complexity Beamforming Designs and Channel Estimation for Passive-Intelligent-Surface-Assisted MISO Energy Transfer

The usage of passive intelligent surface (PIS) is emerging as a low-cost green alternative to massive antenna systems for realizing high energy beamforming (EB) gains. Considering the limited computational capability and constant-envelope precoding for PIS, we propose three novel low-complexity passive EB designs for optimizing the efficacy of PIS-assisted energy transfer (PET) from a multiantenna power beacon (PB) to a single-antenna energy harvesting (EH) user. The first EB design involves solving a univariate equation, and closed forms expressed are presented for the other two. Further, to maximize the practical utility of PET, we introduce a novel channel estimation (CE) protocol for obtaining least-squares estimators for the channels as required for EB designing. Using them, we also derive closed-form expressions for optimal PIS location and optimal time allocation between CE and PET within each coherence block to maximize the user’s net harvested energy. Numerical results verify the CE analysis and validate the novel analytical bound derived for received power during PET and proposed PIS designs’ quality against existing benchmarks. We show that the proposed jointly optimal design for PET can yield a significant improvement of about 15dB, and a reduced active array size at PB can achieve the desired EB gain with sufficient passive elements at PIS. Lastly, we also briefly discuss how the proposed CE and EB designs can be extended to the multiuser settings.